Automated rose cutting in greenhouses with 3D vision and robotics : analysis of 3D vision techniques for stem detection

J.C. Noordam, J. Hemming, C.J.E. van Heerde, F.B.T.F. Golbach, R. van Soest, E. Wekking

    Research output: Contribution to journalArticleAcademicpeer-review

    14 Citations (Scopus)

    Abstract

    The reduction of labour cost is the major motivation to develop a system for robot harvesting of roses in greenhouses that at least can compete with manual harvesting. Due to overlapping leaves, one of the most complicated tasks in robotic rose cutting is to locate the stem and trace the stem down to locate the cutting position. Computer vision techniques like stereo imaging, laser triangulation, röntgen imaging and a new technique, called reverse volumetric intersection, are evaluated in this paper to determine which technique is most feasible for the task. Experiments with the techniques applied on different rose plant indicate that reverse volumetric intersection shows that this technique is most promising to locate the stem down to the cutting position in terms of robustness and costs.
    Original languageEnglish
    Pages (from-to)885-889
    JournalActa Horticulturae
    Volume691
    DOIs
    Publication statusPublished - 2005

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    Rosa
    greenhouses
    stems
    image analysis
    manual harvesting
    methodology
    robots
    computer vision
    lasers
    labor
    leaves

    Cite this

    Noordam, J.C. ; Hemming, J. ; van Heerde, C.J.E. ; Golbach, F.B.T.F. ; van Soest, R. ; Wekking, E. / Automated rose cutting in greenhouses with 3D vision and robotics : analysis of 3D vision techniques for stem detection. In: Acta Horticulturae. 2005 ; Vol. 691. pp. 885-889.
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    title = "Automated rose cutting in greenhouses with 3D vision and robotics : analysis of 3D vision techniques for stem detection",
    abstract = "The reduction of labour cost is the major motivation to develop a system for robot harvesting of roses in greenhouses that at least can compete with manual harvesting. Due to overlapping leaves, one of the most complicated tasks in robotic rose cutting is to locate the stem and trace the stem down to locate the cutting position. Computer vision techniques like stereo imaging, laser triangulation, r{\"o}ntgen imaging and a new technique, called reverse volumetric intersection, are evaluated in this paper to determine which technique is most feasible for the task. Experiments with the techniques applied on different rose plant indicate that reverse volumetric intersection shows that this technique is most promising to locate the stem down to the cutting position in terms of robustness and costs.",
    author = "J.C. Noordam and J. Hemming and {van Heerde}, C.J.E. and F.B.T.F. Golbach and {van Soest}, R. and E. Wekking",
    year = "2005",
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    Automated rose cutting in greenhouses with 3D vision and robotics : analysis of 3D vision techniques for stem detection. / Noordam, J.C.; Hemming, J.; van Heerde, C.J.E.; Golbach, F.B.T.F.; van Soest, R.; Wekking, E.

    In: Acta Horticulturae, Vol. 691, 2005, p. 885-889.

    Research output: Contribution to journalArticleAcademicpeer-review

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    AB - The reduction of labour cost is the major motivation to develop a system for robot harvesting of roses in greenhouses that at least can compete with manual harvesting. Due to overlapping leaves, one of the most complicated tasks in robotic rose cutting is to locate the stem and trace the stem down to locate the cutting position. Computer vision techniques like stereo imaging, laser triangulation, röntgen imaging and a new technique, called reverse volumetric intersection, are evaluated in this paper to determine which technique is most feasible for the task. Experiments with the techniques applied on different rose plant indicate that reverse volumetric intersection shows that this technique is most promising to locate the stem down to the cutting position in terms of robustness and costs.

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